Cooperative face hallucination using multiple references

Authors:
Chih-Chung Hsu;Chia-Wen Lin;Chiou-Ting Hsu;Hong-Yuan Mark Liao
Affiliations:
Department of Electrical Engineering, National Tsing-Hua University;Department of Electrical Engineering, National Tsing-Hua University;Department of Computer Science, National Tsing-Hua University, Hsinchu, Taiwan;Institute of Information Science, Academia Sinica, Nankang, Taipei, Taiwan
Venue:
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Year:
2009

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Abstract

This paper proposes a cooperative example-based face hallucination method using multiple references. The proposed method first uses clustering and residual prototype faces construction to improve the performance of hallucinating a single low-resolution (LR) face to obtain a high-resolution (HR) counterpart. In the case that multiple LR face images for a person are available, a unique feature of the proposed method is to cooperatively enhance the qualities of hallucinated HR images by taking into account the multiple input face images jointly as prior models. Experimental results demonstrate that the proposed cooperative method achieve significant subjective and objective improvement over single-prior schemes.